CBGA-ES+: A Cluster-Based Genetic Algorithm with Non-Dominated Elitist Selection for Supporting Multi-Objective Test Optimization

Many real-world test optimization problems (e.g., test case prioritization) are multi-objective intrinsically and can be tackled using various multi-objective search algorithms (e.g., Non-dominated Sorting Genetic Algorithm (NSGA-II)). However, existing multi-objective search algorithms have certain...

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Bibliographic Details
Published in:	IEEE transactions on software engineering Vol. 47; no. 1; pp. 86 - 107
Main Authors:	Pradhan, Dipesh, Wang, Shuai, Ali, Shaukat, Yue, Tao, Liaaen, Marius
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.01.2021 IEEE Computer Society
Subjects:	Clustering algorithms Clusters Elitism Elitist selection Evolutionary algorithms Genetic algorithms multi-objective genetic algorithm multi-objective test optimization Multiple objective analysis Optimization Randomness search Search algorithms Search problems Sociology Software algorithms Sorting algorithms Statistics
ISSN:	0098-5589, 1939-3520
Online Access:	Get full text
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